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Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data. Models and algorithms are described in <doi:10.1214/07-STS242>, a hands-on tutorial is available from <doi:10.1007/s00180-012-0382-5>. The package allows user-specified loss functions and base-learners.
Version: | 2.9-11 |
Depends: | R (≥ 3.2.0), methods, stats, parallel, stabs (≥ 0.5-0) |
Imports: | Matrix, survival (≥ 3.2-10), splines, lattice, nnls, quadprog, utils, graphics, grDevices, partykit (≥ 1.2-1) |
Suggests: | TH.data, MASS, fields, BayesX, gbm, mlbench, RColorBrewer, rpart (≥ 4.0-3), randomForest, nnet, testthat (≥ 0.10.0), kangar00 |
Published: | 2024-08-22 |
DOI: | 10.32614/CRAN.package.mboost |
Author: | Torsten Hothorn |
Maintainer: | Torsten Hothorn <Torsten.Hothorn at R-project.org> |
BugReports: | https://github.com/boost-R/mboost/issues |
License: | GPL-2 |
URL: | https://github.com/boost-R/mboost |
NeedsCompilation: | yes |
Citation: | mboost citation info |
Materials: | NEWS |
In views: | MachineLearning, Survival |
CRAN checks: | mboost results |
Reference manual: | mboost.pdf |
Vignettes: |
Survival Ensembles (source, R code) mboost (source, R code) mboost Illustrations (source, R code) mboost Tutorial (source, R code) |
Package source: | mboost_2.9-11.tar.gz |
Windows binaries: | r-devel: mboost_2.9-11.zip, r-release: mboost_2.9-11.zip, r-oldrel: mboost_2.9-11.zip |
macOS binaries: | r-release (arm64): mboost_2.9-11.tgz, r-oldrel (arm64): mboost_2.9-11.tgz, r-release (x86_64): mboost_2.9-11.tgz, r-oldrel (x86_64): mboost_2.9-11.tgz |
Old sources: | mboost archive |
Reverse depends: | boostrq, expectreg, FDboost, gamboostLSS, gfboost, InvariantCausalPrediction, tbm |
Reverse imports: | biospear, bujar, carSurv, censored, DIFboost, EnMCB, gamboostMSM, GeDS, geoGAM, mgwrsar, sgboost, visaOTR |
Reverse suggests: | catdata, CompareCausalNetworks, familiar, flowml, fscaret, HSAUR2, HSAUR3, imputeR, MachineShop, MLInterfaces, mlr, pre, spikeSlabGAM, sqlscore, stabs, survex, tidyfit |
Please use the canonical form https://CRAN.R-project.org/package=mboost to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.